IcdarDataset¶
- class mmocr.datasets.IcdarDataset(*args, seg_map_suffix='.png', proposal_file=None, file_client_args=None, backend_args=None, return_classes=False, **kwargs)[源代码]¶
Dataset for text detection while ann_file in coco format.
- 参数
ann_file (str) – Annotation file path. Defaults to ‘’.
metainfo (dict, optional) – Meta information for dataset, such as class information. Defaults to None.
data_root (str) – The root directory for
data_prefix
andann_file
. Defaults to ‘’.data_prefix (dict) – Prefix for training data. Defaults to dict(img_path=’’).
filter_cfg (dict, optional) – Config for filter data. Defaults to None.
indices (int or Sequence[int], optional) – Support using first few data in annotation file to facilitate training/testing on a smaller dataset. Defaults to None which means using all
data_infos
.serialize_data (bool, optional) – Whether to hold memory using serialized objects, when enabled, data loader workers can use shared RAM from master process instead of making a copy. Defaults to True.
pipeline (list, optional) – Processing pipeline. Defaults to [].
test_mode (bool, optional) –
test_mode=True
means in test phase. Defaults to False.lazy_init (bool, optional) – Whether to load annotation during instantiation. In some cases, such as visualization, only the meta information of the dataset is needed, which is not necessary to load annotation file.
Basedataset
can skip load annotations to save time by setlazy_init=False
. Defaults to False.max_refetch (int, optional) – If
Basedataset.prepare_data
get a None img. The maximum extra number of cycles to get a valid image. Defaults to 1000.